Margie Doyle and Andrew Forney Loyola Marymount University 10/19/10 GenMAPP 2 Margie Doyle and Andrew Forney Loyola Marymount University 10/19/10

Goal and Outline Goal: To familiarize the audience with the uses and nuances of GenMAPP 2 Background and main application of GenMAPP 2 Application structure and composition Improvements of GenMAPP 2 over predecessor Future directions of GenMAPP 2

Bridge gap between data and respective biological processes GenMAPP Responds to Biologists’ Needs Developing need of biologists to visualize and analyze complex genomics Bridge gap between data and respective biological processes Pathway-oriented data examination GenMAPP 2’s Main Result: Visually rich, easy to use application for genomic analysis and data sharing

Programmed in Visual Basic 6.0 Three primary file categories GenMAPP’s File Structure is Specialized Programmed in Visual Basic 6.0 Three primary file categories Experimental data (.gex) Gene databases (.gdb) Pathways (.mapp) Data sharing enabled by “Data Acquisition Tool” within GenMAPP

Improvements Focus on Analysis and Sharing New database organization better connects user data to existing archives New visualization tools to enable simultaneous viewing of multiple datasets New export capabilities for ease of sharing information and data

Homology MAPPs Provide a Basis for Analysis Various species can be mapped using preexisting human pathway data (Figure 1) There are limitations to the conversion process for certain species (Figure 2, Table 1)

Figure 1

Figure 2

Inter-Database Pathway Extension Improves Content Because of overlap with many databases (like Gene Ontology), extraction can expand GenMAPP records (Figure 3) Possible extraction can be for coexpression or transcriptional regulation as well (Figure 4)

Figure 3

Figure 4

Improved Visualization of Data Allows for Clearer Analysis GenMAPP 2 allows for clear analysis of multiple time-point comparisons, even simultaneously (Figure 5) New feature to view multiple data types as a cohesive view all in one window (Figure 6)

Figure 5

Figure 6

Future Directions of GenMAPP Reach for Efficiency / Expansion Obstacle: Windows only Solution: Java-based implementation Obstacle: Genetic feature representation Solution: Dynamic organization of records Obstacle: More efficient pathway vocabularies Solution: Better analysis methods / tools

GenMAPP 2 connects and serves the community of biologists with powerful tools to visually interpret and juxtapose complex genetic information

References Salomonis N, Hanspers K, Zambon AC, Vranizan K, Lawlor SC, Dahlquist KD, Doniger SW, Stuart J, Conklin BR, and Pico AR. GenMAPP 2: new features and resources for pathway analysis. BMC Bioinformatics 2007 Jun 24; 8 217. doi:10.1186/1471-2105-8-217 pmid:17588266.